Best AI tools for< Understand Drug Risks >

xAI Grok is a visual analytics platform that helps users understand and interpret machine learning models. It provides a variety of tools for visualizing and exploring model data, including interactive charts, graphs, and tables. xAI Grok also includes a library of pre-built visualizations that can be used to quickly get started with model analysis.

Brandwatch is a social media management and analytics platform that helps businesses understand and engage with their customers. It offers a range of features, including social listening, influencer marketing, and content management. Brandwatch is used by some of the world's largest brands, including Virgin Holidays, OnePlus, and Metia.

Sourcegraph is a code intelligence platform that helps developers write, fix, and maintain code faster. It uses artificial intelligence to understand the code graph and provide insights that help developers focus on writing and shipping code. Sourcegraph is used by over 2.5 million engineers at companies like Google, Amazon, and Microsoft.

Digimind is an intelligence software platform that provides solutions for brand reputation, competitive intelligence, consumer insights, influencer identification, trend tracking, and campaign analysis. It leverages Artificial Intelligence (AI) to collect and analyze billions of content pieces, offering real-time market intelligence and helping users fully understand consumer insights and market trends. The platform is trusted by global brands and agencies, offering easy-to-read, up-to-date analysis and reports. Digimind's AI Sense technology provides automated curation and recommended actions, delivering compelling reports instantly.

Explainpaper is an AI tool designed to simplify and explain dense sections of research papers, making them easy to read and understand. Users can upload a paper, highlight confusing text, and receive explanations generated by an AI model. The tool aims to reduce the time spent on reviewing research papers and help users comprehend complex concepts more effectively.

InstantPersonas is an AI-powered tool that allows users to generate detailed user personas in seconds. It helps marketers and business owners understand their audience better by providing real-time insights into the thoughts of their audience. With InstantPersonas, users can create persona-driven content that resonates with their target audience, ultimately improving their content creation process and marketing strategies. The tool offers industry-leading AI capabilities at an affordable price, making it a valuable asset for businesses looking to enhance their marketing efforts.

PandaChat is a suite of AI-powered products designed to enhance productivity and streamline communication. It offers a range of tools for both personal and business use, including: - PandaChat Assistant: A virtual assistant that can chat with users, summarize articles, and answer questions based on uploaded documents or online content. - PandaChat Live: A platform for embedding chatbots on websites, providing personalized support and enhancing user experience. - Hai News: An AI tool that allows users to chat with news articles, providing summaries and insights on specific topics. - Hai Surf: An AI tool that enables users to chat with any web content, extracting information and answering questions. PandaChat is committed to data security and privacy, giving users control over their data and offering on-premises installation for businesses. It has been recognized for its innovation, winning the AI/Machine Learning Innovation of the Year award at the SDC Awards.

Opnbx is a bespoke revenue operating platform that helps sales teams understand their target market and prioritize their sales and marketing efforts. It uses AI to learn from a company's revenue team and scour billions of data points to give a real-time view of the market. Opnbx also provides insights into which companies are in buying mode right now and which prospects are visiting a company's website in real-time. It provides persona and contact details, including mobile numbers and email addresses, and has an AI email writing platform that provides the right research to create personalized and relevant messages in seconds.

Theodore AI is an AI-powered tool that helps users understand complex topics quickly and easily. With just three clicks, users can get a clear and concise explanation of any topic, making it perfect for students, researchers, and anyone who wants to learn something new.

SiteExplainer is an AI-powered web application that helps users understand the purpose of any website quickly and accurately. It uses advanced artificial intelligence and machine learning technology to analyze the content of a website and present a summary of the main ideas and key points. SiteExplainer simplifies the language used on landing pages and eliminates corporate jargon to help visitors better understand a website's content.

Menu Mystic is an AI-powered tool designed to help users understand and navigate restaurant menus with ease. By simply scanning a menu, users can access detailed explanations for each dish, along with wine and dessert pairing recommendations. The tool utilizes advanced AI and image recognition technology to enhance the dining experience, making it easier for users to explore diverse cuisines and make informed choices at restaurants.

EmpathixAI is an innovative AI tool designed to analyze and interpret human emotions through text and voice inputs. The tool uses advanced natural language processing and sentiment analysis algorithms to provide accurate insights into the emotional state of individuals. EmpathixAI helps businesses understand customer feedback, improve communication strategies, and enhance user experiences. With its user-friendly interface and powerful analytics capabilities, EmpathixAI is a valuable tool for companies looking to gain a deeper understanding of customer sentiment and emotions.

Sequel is an AI-powered tool that serves as a natural language interface for databases, allowing users to effortlessly navigate and understand their data without the need to write complex SQL queries. By simply asking questions in plain English, users can quickly obtain insights and visualizations from their database. The tool supports a wide range of databases and services, ensuring users can connect to their existing database securely and efficiently. Sequel's AI capabilities enable users to generate SQL queries, uncover insights, and make better decisions based on the data analysis.

Memenome AI is an AI tool that helps users discover and understand trending sounds, hashtags, accounts, and posts on TikTok. It offers features to find top sounds, hashtags, and posts, provides AI analysis and templates for trend understanding, and allows users to iterate through content ideas with Meme0. The tool aims to save users time by efficiently identifying trends and empowering them to create engaging content.

Hive AI provides a suite of AI models and solutions for understanding, searching, and generating content. Their AI models can be integrated into applications via APIs, enabling developers to add advanced content understanding capabilities to their products. Hive AI's solutions are used by businesses in various industries, including digital platforms, sports, media, and marketing, to streamline content moderation, automate image search and authentication, measure sponsorships, and monetize ad inventory.

Code to Flowchart is an AI-powered tool that helps users visualize and understand program logic instantly. It allows users to convert code into interactive flowcharts with the help of AI analysis. The tool supports all major programming languages, identifies code paths and logic flows, and offers multiple visualization options like flowcharts, sequence diagrams, and class diagrams. Users can export diagrams in various formats and customize color schemes and themes. Code to Flowchart aims to simplify complex code structures and enhance collaboration among developers.

Excelly-AI is a powerful tool that transforms plain text into Excel formulas, supporting both Excel and Google Sheets. Users can generate any formula they like and receive explanations for each. It allows uploading .xlsx files for personalized prompts and offers VBA formula generation. Excelly-AI integrates with Slack for team collaboration and provides column schema support for meaningful prompts, enhancing Excel and Google Sheets operations.

OpenSpace is a reality capture and construction site capture application that utilizes AI-powered analytics to help builders from preconstruction to operations. It offers unmatched speed and simplicity in capturing sites, automatically mapping photos to plans with its Spatial AI engine. The application provides a complete, as-built record of buildings, improves coordination, reduces risk, and enhances communication through features like BIM Compare, Split View, Field Notes, and integrations with project management software. OpenSpace has been trusted by industry leaders globally, capturing billions of square feet and images across thousands of projects in over 95 countries.

Linfo.ai is an AI-powered Article & Youtube Summary & Mind Map tool with GPT Extension that provides users with instant summaries and structured insights from articles, reports, and videos. It allows users to dive deep into any topic, surface valuable insights effortlessly, and customize content hierarchy for quick navigation and comprehension. The tool is designed for professionals who need to process information quickly and efficiently.

TheySaid is a Conversational AI Survey tool that helps businesses drive customer value and revenue through AI-powered surveys. It offers a unique approach of engaging audiences with one relevant question at a time, turning feedback into an ongoing dialogue. The AI tool scans websites to generate tailored survey questions, automates follow-ups with customers, and provides actionable insights based on industry standards and best practices. TheySaid's AI digs deeper by asking personalized follow-up questions in real-time, enhancing customer engagement and satisfaction.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

This repository is a curated list of research papers that explore the integration of Large Language Model (LLM) technology with tabular data. It aims to provide a comprehensive resource for researchers and practitioners interested in this emerging field. The repository includes papers on a wide range of topics, including table-to-text generation, table question answering, and tabular data classification. It also includes a section on related datasets and resources.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

The Ersilia Model Hub is a unified platform of pre-trained AI/ML models dedicated to infectious and neglected disease research. It offers an open-source, low-code solution that provides seamless access to AI/ML models for drug discovery. Models housed in the hub come from two sources: published models from literature (with due third-party acknowledgment) and custom models developed by the Ersilia team or contributors.

This repository serves as an educational resource for pharmaceutical and chemistry students to learn the basics of Deep Learning through a collection of Jupyter Notebooks. The content covers various topics such as Introduction to Jupyter, Python, Cheminformatics & RDKit, Linear Regression, Data Science, Linear Algebra, Neural Networks, PyTorch, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks, Autoencoders, Graph Neural Networks, and Summary. The notebooks aim to provide theoretical concepts to understand neural networks through code completion, but instructors are encouraged to supplement with their own lectures. The work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

This repository is a collection of papers on leveraging Large Language Models (LLMs) in Graph Tasks. It provides a comprehensive overview of how LLMs can enhance graph-related tasks by combining them with traditional Graph Neural Networks (GNNs). The integration of LLMs with GNNs allows for capturing both structural and contextual aspects of nodes in graph data, leading to more powerful graph learning. The repository includes summaries of various models that leverage LLMs to assist in graph-related tasks, along with links to papers and code repositories for further exploration.

A collection of papers and resources about Large Language Models (LLM) for Graph Learning (Graph). Integrating LLMs with graph learning techniques to enhance performance in graph learning tasks. Categorizes approaches based on four primary paradigms and nine secondary-level categories. Valuable for research or practice in self-supervised learning for recommendation systems.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

PearAI Submodule / Extension is the source code for the bulk of PearAI's functionality, bundled as a VSCode / PearAI extension. It allows users to easily understand code sections, refactor functions, and ask questions by mentioning a file. The tool aims to enhance coding experience and productivity within the VSCode environment.

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